DOI: 10.1051/proc:071912
Combined use of importance weights and resampling weights in sequential Monte Carlo methods
Francois Le GlandIRISA / INRIA, Campus de Beaulieu, 35042 RENNES Cédex, France
(Published online: 30 October 2007)
Abstract
A particle approximation of Feynman-Kac distributions is presented
here, that combines SIS and SIR algorithms in the sense that only
a part of the importance weights is used for resampling, and
two different approaches are proposed to analyze its performance.
The first approach is based on a representation in terms of path-space
distributions, and could be used to analyze the joint particle
approximation of distributions for a reference model and several
alternate models at the same time.
The second approach, which is of independent interest and seems
very promising, is based on a representation in terms of a multiplicative
functional, and could be used to analyze particle approximation with
adaptive resampling schemes.
© EDP Sciences, ESAIM 2007


BibSonomy
CiteUlike
Connotea
Del.icio.us
Digg
Facebook